Solution Engineer

distil labs; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Distil Labs is seeking a seasoned Customer Delivery Engineer to guide engagements from initial technical kickoff through production rollout. You will align evaluation criteria, configure data pipelines, and lead training and assessment efforts to ensure models meet customer benchmarks.

In this remote-friendly role, you’ll collaborate with cross-functional teams, maintain clear communications, and drive improvements based on real-world field learnings, helping customers adopt high-quality AI

Qualifications

• Five+ years in a technical, customer-facing role such as solutions engineering, implementation, forward-deployed engineering, or AI customer engineering.
• Hands-on experience with language models in production, including prompting, evaluation, and diagnosing failures at scale.
• Comfort with traces, structured data files, configuration formats, and command-line tools.
• Experience designing and running evaluations for language-model systems.
• Fluent English and clear, calm written communication.

Responsibilities

• Own the customer delivery journey after a technical engagement begins, delivering models that meet customers' tests.
• Prepare data and job descriptions, configure processing, launch training, interpret results, and iterate on quality improvements.
• Run engagements with clear timelines, regular updates, early blocker escalation, and controlled production rollout.
• Build customer confidence through transparent communication and honest assessments of model performance.
• Operate the platform at an expert level and identify workflow improvements for the developer- and agent-facing interface.
• Convert field learnings into concrete requests that improve the product for faster later engagements.

Skills

Solutions engineering

AI in production

Prompting & evaluation

Project management

English communication

Job description

Role overview

Own the customer delivery journey after a technical engagement begins, helping turn production workloads into reliable custom models. The role combines solution engineering, model evaluation, project management, and product feedback: success is measured by whether a model meets the customer’s standards and is adopted in production.

Responsibilities

• Agree evaluation criteria and acceptance thresholds with customers, then deliver models that meet their own tests.
• Prepare data and job descriptions, configure processing, launch training, interpret results, and iterate on quality improvements.
• Run engagements with clear timelines, regular written updates, early blocker escalation, and a controlled production rollout.
• Build customer confidence through transparent communication and honest assessments of model performance.
• Operate the platform at expert level and identify workflow improvements for the developer- and agent-facing interface.
• Convert field learnings into concrete requests that improve the product and make later engagements faster.

Requirements

• At least five years in a technical, customer-facing role such as solutions engineering, implementation, forward-deployed engineering, or AI customer engineering.
• Hands-on experience with language models in production, including prompting, evaluation, and diagnosing failures at scale.
• Comfort working with traces, structured data files, configuration formats, and command-line tools.
• Experience designing and running evaluations for language-model systems.
• Fluent English and clear, calm written communication.
• Strong ownership, customer focus, curiosity, prioritization, and project-management skills.

Nice to have

• Startup experience as an early employee or technical founder.
• Experience with agent-facing tools, model fine-tuning, distillation, or small-model trade-offs.
• Familiarity with agentic workflows and structured tasks such as classification, extraction, routing, or tool calling.

Benefits and work setup

• Fully remote across Europe, with occasional team travel.
• High ownership, direct access to senior decision-makers, and an opportunity to shape the solution-engineering function.